The AI race heats up: Google announces PaLM 2, its answer to GPT-4


On Wednesday, Google launched PaLM 2, a household of foundational language fashions akin to OpenAI’s GPT-4. At its Google I/O occasion in Mountain View, California, Google revealed that it already makes use of PaLM 2 to energy 25 merchandise, together with its Bard conversational AI assistant.

As a household of huge language fashions (LLMs), PaLM 2 has been educated on an infinite quantity of knowledge and does next-word prediction, which outputs the almost definitely textual content after a immediate enter by people. PaLM stands for “Pathways Language Mannequin,” and “Pathways” is a machine-learning approach created at Google. PaLM 2 follows up on the original PaLM, which Google introduced in April 2022.

In response to Google, PaLM 2 helps over 100 languages and may carry out “reasoning,” code era, and multi-lingual translation. Throughout his 2023 Google I/O keynote, Google CEO Sundar Pichai mentioned that PaLM 2 is available in 4 sizes: Gecko, Otter, Bison, Unicorn. Gecko is the smallest and may reportedly run on a cell system. Apart from Bard, PaLM 2 is behind AI options in Docs, Sheets, and Slides.

A Google-provided example of PaLM 2
Enlarge / A Google-provided instance of PaLM 2 “reasoning.”


All that’s fantastic and effectively, however how does PaLM 2 stack as much as GPT-4? Within the PaLM 2 Technical Report, PaLM 2 appears to beat GPT-4 in some mathematical, translation, and reasoning duties. However actuality may not match Google’s benchmarks. In a cursory analysis of the PaLM 2 model of Bard by Ethan Mollick, a Wharton professor who usually writes about AI, Mollick finds that PaLM 2’s efficiency seems worse than GPT-4 and Bing on varied casual language exams, which he detailed in a Twitter thread.

Till lately, the PaLM household of language fashions has been an inner Google Analysis product with no client publicity, however Google started offering limited API access in March. Nonetheless, the primary PaLM was notable for its huge dimension: 540 billion parameters. Parameters are numerical variables that function the discovered “information” of the mannequin, enabling it to make predictions and generate textual content primarily based on the enter it receives.

A Google-provided example of PaLM 2 translating languages.
Enlarge / A Google-provided instance of PaLM 2 translating languages.


Extra parameters roughly means extra complexity, however there isn’t any assure they’re used effectively. By comparability, OpenAI’s GPT-3 (from 2020) has 175 billion parameters. OpenAI has by no means disclosed the variety of parameters in GPT-4.

In order that results in the massive query: Simply how “massive” is PaLM 2 by way of parameter depend? Google doesn’t say, which has annoyed some industry experts who usually combat for extra transparency in what makes AI fashions tick.

That is not the one property of PaLM 2 that Google has been quiet about. The corporate says that PaLM 2 has been educated on “a various set of sources: net paperwork, books, code, arithmetic, and conversational knowledge,” however doesn’t go into element about what precisely that knowledge is.

As with different massive language mannequin datasets, the PaLM 2 dataset doubtless contains all kinds of copyrighted material used with out permission and probably dangerous materials scraped from the Web. Coaching knowledge decisively influences the output of any AI mannequin, so some consultants have been advocating using open data sets that may present alternatives for scientific reproducibility and moral scrutiny.

A Google-provided example of PaLM 2 writing program code.
Enlarge / A Google-provided instance of PaLM 2 writing program code.


“Now that LLMs are merchandise (not simply analysis), we’re at a turning level: for-profit corporations will turn out to be much less and fewer clear *particularly* in regards to the parts which are most necessary,” tweeted Jesse Dodge, a analysis scientist on the Allen Institute of AI. “Provided that the open supply group can arrange collectively can we sustain!”

To date, criticism of hiding its secret sauce hasn’t stopped Google from pursuing extensive deployment of AI fashions, regardless of an inclination in all LLMs to only make things up out of skinny air. Throughout Google I/O, firm reps demoed AI options in many of its major products, which suggests a broad swath of the general public may very well be battling AI confabulations quickly.

And so far as LLMs go, PaLM 2 is much from the tip of the story: Within the I/O keynote, Pichai talked about {that a} newer multimodal AI mannequin known as “Gemini” was presently in coaching. Because the race for AI dominance continues, Google customers within the US and 180 other countries (oddly excluding Canada and mainland Europe) can try PaLM 2 themselves as a part of Google Bard, the experimental AI assistant.

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